Semantic query caching in a mobile environment

ABSTRACT

Caching of remote data in a mobile client's local storage can improve data access performance and data availability. Traditional approaches are page-based, without taking advantage of the semantics of cached data. It is difficult for a client to determine if a query could be answered entirely based on locally cached data, forcing it to contact the database server for additional data. We propose a semantic caching mechanism which allows data to be cached as a collection of possibly related blocks, each of which is the result of a previously evaluated query. We investigate mechanisms for transforming projection-selection queries to reuse cached data blocks. This avoids transmitting unwanted data items over low bandwidth wireless channels. Cache replacement techniques based on the semantics of cached data are also proposed. We describe the design of our prototype and study its performance.

REFERENCES

• 1: B.R. Badrinath and S.H. Phatak. An Architecture for Mobile Databases. Technical Report DCS-TR-351, Department of Computer Science, Rutgers University.
• 2: Daniel Barbará , Tomasz Imieliński, Sleepers and workaholics: caching strategies in mobile environments, Proceedings of the 1994 ACM SIGMOD international conference on Management of data, p.1-12, May 24-27, 1994, Minneapolis, Minnesota, United States
• 3: Michael J. Carey , Michael J. Franklin , Miron Livny , Eugene J. Shekita, Data caching tradeoffs in client-server DBMS architectures, Proceedings of the 1991 ACM SIGMOD international conference on Management of data, p.357-366, May 29-31, 1991, Denver, Colorado, United States
• 4: Boris Y. L. Chan , Antonio Si , Hong Va Leong, Cache Management for Mobile Databases: Design and Evaluation, Proceedings of the Fourteenth International Conference on Data Engineering, p.54-63, February 23-27, 1998
• 5: Surajit Chaudhuri , Ravi Krishnamurthy , Spyros Potamianos , Kyuseok Shim, Optimizing Queries with Materialized Views, Proceedings of the Eleventh International Conference on Data Engineering, p.190-200, March 06-10, 1995
• 6: Latha S. Colby , Akira Kawaguchi , Daniel F. Lieuwen , Inderpal Singh Mumick , Kenneth A. Ross, Supporting multiple view maintenance policies, Proceedings of the 1997 ACM SIGMOD international conference on Management of data, p.405-416, May 11-15, 1997, Tucson, Arizona, United States
• 7: Shaul Dar , Michael J. Franklin , Björn Þór Jónsson , Divesh Srivastava , Michael Tan, Semantic Data Caching and Replacement, Proceedings of the 22th International Conference on Very Large Data Bases, p.330-341, September 03-06, 1996
• 8: Prasad M. Deshpande , Karthikeyan Ramasamy , Amit Shukla , Jeffrey F. Naughton, Caching multidimensional queries using chunks, Proceedings of the 1998 ACM SIGMOD international conference on Management of data, p.259-270, June 01-04, 1998, Seattle, Washington, United States
• 9: Himanshu Gupta, Selection of Views to Materialize in a Data Warehouse, Proceedings of the 6th International Conference on Database Theory, p.98-112, January 08-10, 1997
• 10: Yixiu Huang , Prasad Sistla , Ouri Wolfson, Data replication for mobile computers, Proceedings of the 1994 ACM SIGMOD international conference on Management of data, p.13-24, May 24-27, 1994, Minneapolis, Minnesota, United States
• 11: Magdi N. Kamel , Susan B. Davidson, Semi-materialization: a technique for optimizing frequently executed queries, Data & Knowledge Engineering, v.6 n.2, p.101-123, March 1991 [doi>10.1016/0169-023X(91)90018-S]
• 12: Ken C. K. Lee , Antonio Si , Hong V. Leong, Incremental view update for a mobile data warehouse, Proceedings of the 1998 ACM symposium on Applied Computing, p.394-399, February 27-March 01, 1998, Atlanta, Georgia, United States [doi>10.1145/330560.330846]
• 13: Xiaolei Qian, Query Folding, Proceedings of the Twelfth International Conference on Data Engineering, p.48-55, February 26-March 01, 1996
• 14: Jian Yang , Kamalakar Karlapalem , Qing Li, Algorithms for Materialized View Design in Data Warehousing Environment, Proceedings of the 23rd International Conference on Very Large Data Bases, p.136-145, August 25-29, 1997